Insulin-like growth factor binding protein 2: a core biomarker of left ventricular dysfunction in dilated cardiomyopathy

作者全名："Yu, Wei; Gao, Hongli; Hu, Tianyang; Tan, Xingling; Liu, Yiheng; Liu, Hongli; He, Siming; Chen, Zijun; Guo, Sheng; Huang, Jing"

作者地址："[Yu, Wei; Gao, Hongli; Chen, Zijun] Chongqing Med Univ, Dept Cardiol, Yongchuan Hosp, Chongqing, Peoples R China; [Yu, Wei; Tan, Xingling; Liu, Yiheng; Liu, Hongli; He, Siming; Huang, Jing] Chongqing Med Univ, Affiliated Hosp 2, Dept Cardiol, Chongqing, Peoples R China; [Hu, Tianyang] Chongqing Med Univ, Affiliated Hosp 2, Precis Med Ctr, Chongqing, Peoples R China; [Guo, Sheng] Peoples Hosp Rongchang Dist, Dept Cardiol, Chongqing, Peoples R China"

通信作者："Huang, J (通讯作者)，Chongqing Med Univ, Affiliated Hosp 2, Dept Cardiol, Chongqing, Peoples R China.; Guo, S (通讯作者)，Peoples Hosp Rongchang Dist, Dept Cardiol, Chongqing, Peoples R China."

来源：HEREDITAS

ESI学科分类：MOLECULAR BIOLOGY & GENETICS

WOS号：WOS:001089818600001

JCR分区：Q3

影响因子：2.1

年份：2023

卷号：160

期号：1

开始页：　

结束页：　

文献类型：Article

关键词：Dilated cardiomyopathy; RNA modifications; Machine learning; IGFBP2; Left ventricular ejection fraction

摘要："BackgroundRNA modifications, especially N6-methyladenosine, N1-methyladenosine and 5-methylcytosine, play an important role in the progression of cardiovascular disease. However, its regulatory function in dilated cardiomyopathy (DCM) remains to be undefined.MethodsIn the study, key RNA modification regulators (RMRs) were screened by three machine learning models. Subsequently, a risk prediction model for DCM was developed and validated based on these important genes, and the diagnostic efficiency of these genes was assessed. Meanwhile, the relevance of these genes to clinical traits was explored. In both animal models and human subjects, the gene with the strongest connection was confirmed. The expression patterns of important genes were investigated using single-cell analysis.ResultsA total of 4 key RMRs were identified. The risk prediction models were constructed basing on these genes which showed a good accuracy and sensitivity in both the training and test set. Correlation analysis showed that insulin-like growth factor binding protein 2 (IGFBP2) had the highest correlation with left ventricular ejection fraction (LVEF) (R = -0.49, P = 0.00039). Further validation expression level of IGFBP2 indicated that this gene was significantly upregulated in DCM animal models and patients, and correlation analysis validation showed a significant negative correlation between IGFBP2 and LVEF (R = -0.87; P = 6*10-5). Single-cell analysis revealed that this gene was mainly expressed in endothelial cells.ConclusionIn conclusion, IGFBP2 is an important biomarker of left ventricular dysfunction in DCM. Future clinical applications could possibly use it as a possible therapeutic target."

基金机构：Not applicable.

基金资助正文：Not applicable.